The Smart Data Potential : How does contextual intelligence help in dealing with serious incidents ?

August 24th, 2016

In the context of its international growth strategy and with the upcoming major sporting events being held in Japan, OpenField is working with its strategic partners as well as with international players such as Mitsui & Co (Paris branch), one of the first Sogo Shosha in Japan, in order to promote its innovation. Based on its vision and its know-how in terms of the convergence between digital and physical data, OpenField provides an outline in this article of instances of the use of behavioural data in a variety of sectors and the resulting value created. Given the enormous potential here, OpenField demonstrates how this contextual intelligence can be used to serve the needs of crisis management for serious incidents through the example of an incident occurring in the vicinity of a major sporting event in Japan.

Our vision

The physical spaces we are familiar with and use every day – from offices and shopping centres to sports venues, and including the various rooms of our homes, – are being radically changed by new levels of interconnection between the physical and the digital worlds. New technologies such as geolocation, new exchange protocols such as the Internet of Things, new generation sensors, etc. making it possible to acquire ever greater volumes of data relating to how people behave and how spaces are used. In addition, digital technologies that relate in particular to mobility are making their presence felt in these spaces as new points of interaction with individuals.

These new interconnections apply to every area of activity in which companies operate.

We are aiming, with OpenField, to support companies through this change, by helping them develop a better understanding of individuals, their behaviour, their interactions with their environments and how they use the spaces in which they live, work or visit.

We guarantee regulatory compliance, security and transparency in the use of personal data, whilst identifying the needs of each individual and the best way of meeting, and anticipating these.

Such detailed and real-time knowledge of behaviours and uses is going to help companies optimise their assets, as well as create new ones, to identify new products or new services and achieve a better measurement of performances.

Our Expertise

OpenField offers an innovative solution making it possible to analyse and enhance the experiences of visitors to “connected” spaces. Using this we build contextual intelligence on our customers. We synchronously collect and analyse, using our Data Management Platform, all interaction data. An interaction point can be an access control system, a Wifi socket, an interactive socket, a payment or loyalty card terminal, a website, a mobile app, a building’s technical management systems, etc. Our algorithms allow us to turn this data into behavioural and geolocation information, generating a real-time tracking that allows a prediction of behaviours and needs. Our data visualisation solution means that detailed analyses are available in the form of management charts or plans and enable the sharing of all the value of invested capital.

The functionalities of our integrated CRM solution include the use of the collected data to develop personalised proposals (E.g.: Write to all the women who connect to the Wifi in the Fashion area of the shopping centre, or write to all the fans who arrive at the venue before 17:00, etc.). All the declared or consumption and behavioural data on the “customers” are used with the aim of creating an extremely accurate targeting. Every geolocated transaction collected from the points of contact becomes a potential trigger in these campaigns thanks to the synchronous nature of the exchanges.

We can also offer a range of algorithms. There is an algorithm that converts physical information to reconstruct the routes followed by visitors or spectators through a space. Others, which, depending of the context data, predict how the visitor will behave, or will want, next (E.g.: propensity for the consumption of a new service, the likelihood of further visits, the risk of a “no-show”, etc.). This new information is used in generating the offers that can be pushed by the CRM tool, whether communicated by email, SMS, push notification, or dynamic display on a portal or digital wall.

Finally, we are currently studying new use instances based around the Internet of Things in homes. We believe we can find new levers for enhancing experiences and/or optimising residential and work space flows.

We have core strategic partnerships with Microsoft, Cisco, Accenture and France’s Altarea Cogedim group. We are a start-up, a member of the “French Tech” digital exchange community supported by the French government and industry, and we are in the process of setting up in the United States. We currently work in a number of business spheres: sports, entertainment, cultural and event venues, shopping centres and hotel and theme park environments.

Use Case

Optimising the customer/spectator experience at the stadium

By collecting, in real-time, ticketing, access control, snack bar or shop consumption data, as well as data on sporting competitions, the weather, traffic, TV programmes and school holidays, and even religious holidays, we enabled the club or the venue operator to accurately and quickly obtain an understanding of spectator behaviour and to measure in detail the impact of the Marketing and sales initiatives. We were thus able to help these teams effectively achieve their key goals of maximising income and filling the stadium.

We were able to help the Marketing team in finding answers to various questions:

How can we identify “no-show” tickets, i.e. people who have a ticket (often in the context of a season ticket) but who will not come to the next match?

By understanding the customer: Analysing the customer’s behavioural history relating to sporting events, the opponents, place of residence, weather, match day evening traffic, holidays, etc. (250 criteria processed) allowed us to develop a predictive algorithm to calculate a probability of attendance at the next match.

Benefits or corrective actions: Based on the calculated score, the club will either point the ticket holder towards a ticket exchange platform or offer the person an Up-Sell of an alternative experience in a “Linked in” box to meet people, for instance, working in the same professional field.

Optimising asset management

All of this behavioural information however has a dual value. Beyond the customer experience, it also offers the possibility of optimising the management of the assets.

This makes it possible to adjust the allocation of space within the shopping centre in the light of the flows for cells (shops) and the targeted routes of visitors. We can analyse, relative to a brand, the reasons for the lack of appeal of its sales outlet. We can, using the estimated uses and frequentation, anticipate the strategic parameters for the building: Energies, entry and exit paths, control systems, etc.

As a general rule, just because a space has been designed in a certain way does not mean that people will use it exactly as intended in the plans.

To summarise

The potential offered by data is fantastic. We are certain that the Internet of Things, with new sensors, will make it possible to define additional, very high added value, services. Our position in this right from the start, has been as a driving force and strongbox for our customers’ data.

First of all, GAFA (Google, Apple, Facebook, Amazon) are ready to spend large amounts of money to penetrate into private spaces and enclosures. Our customers understand that they need to retain ownership of their data and their relationships with their visitors, users or consumers. We work with them to develop this capital and to guarantee its quality and security. We are therefore seen by them as a Trusted Third Party.

Secondly, individuals, who are being increasingly targeted by traditional and digital conversation channels, want to be able to retain control over and protect their privacy. The systems of legal protection in France and Europe are fairly advanced and we aim to act in an exemplary manner concerning these. This is what we like to call our Green Data policy. Our future depends totally on our everyday observance of this policy.

Transition

We are currently focused, together with our customers, on using data with the aim of prolonging the length of the route through their spaces and on ensuring a rapid return by their visitors and consumers.

Using the same data sources and the same communication channels, we will also in the future be able to use this information to ensure the fastest possible evacuation of visitors in the event of a serious incident: Terrorist attack, earthquake, unexpected major structural failure or quite simply any hazardous crowd movement. A stadium has the capacity to hold 60,000 inhabitants of a city on a single site. The areas involved are also significant for a shopping centre that receives 150,000 unique visitors a month.

How does contextual intelligence help in dealing with serious incidents?

The granularity of the data we collect means we can identify weak signals within the data lake. Our algorithms enable us to predict how the key parameters will evolve.

Public open data integrated into our databases helps provide an additional level of contextual intelligence: We know what is happening in the connected spaces, as well as in the vicinity of these. Taking into account the state of the external environment, in the same way as for the internal context, we will be able to optimise any evacuation of the space.

Our CRM solutions make it possible to draw up communication scenarios based on a variety of incidents and to act with individuals in real-time. We can thus alert, inform, direct, etc.

This data on the numbers of individuals in the space also means that we can identify those who are no longer responding to instructions (injured, buried, etc.) and determine priority actions.

Let’s consider a scenario:

19:00: 30% of spectators have entered the stadium, the rugby match kick-off is at 20:30. The situation is normal and everything is as would be expected for a rainy Friday evening match. We know how many people have come in through each gate in real-time thanks to the access monitoring. Every spectator arriving before 19:00 has been offered a voucher for a Happy Hour at the snack bar. For the boxes, screens welcoming the VIPs are installed in the lounges.

19:15: Warnings from the building technical management system are showing a rise in abnormal indicators in the Northeast gate sector. In addition, no automatic checking of tickets has taken place on the 10 automatic barriers for a period of 30 seconds. The information is fed to the control centre for rapid verification.

19:17: The first messages indicating an incident having damaged the gates in the Northeast sector are received.

19:20: An initial analysis identifies how many spectators are still expected through that sector. Vehicle traffic is getting heavier and public transport continues to deliver people to the stadium concourse.

19:25: A danger of escalation is quickly isolated; the match will continue.
With regard to the expected flows, additional security cover is quickly requested for the site of the incident as well as at the adjacent gates and the public transport drop-off points in order to manage the additional flows of spectators in the zones. The access control system is automatically updated in order to accept tickets that should otherwise have been checked at gates that are no longer operational.

19:27: Applying a defined communication plan based on the nature of the incident, SMS, email and push notification messages are sent to all spectators who are expecting to enter the stadium through the inoperative sector in order to redirect them, based on their seat numbers, to nearby gates. The map available on the mobile app is instantly updated to show that the gates in the sector are closed and the alternative routes to be followed to access the stadium according to seat locations.

19:30: The catering outlets in the affected sector are evacuated, the products are moved to other nearby sales outlets. The dynamic information screens inform consumers they need to go to the alternative sales outlets based on observed waiting times.

19:55: 80% of spectators have entered and flows are normal for 35 minutes prior to kick-off, the impact of the incident has been controlled.

20:55: 25 minutes after kick-off, and once everyone is seated, with the flows detected at the access points being zero, SMS, email and push notifications messages are sent to the affected spectators to inform them of which exit routes to use after the match, based on their chosen method of travel.

22:30: 30 minutes after the end of the match, reminder SMS, email and push notification messages are sent to any spectators detected through Wifi and near the affected zone. The dynamic screens also provide information on the exit routes from the stadium.

Conclusion

The future promises us an increasingly “connected” environment, in which “physical” data will supersede digital data. Beyond the “Big Data” phenomena, data collected and processed in real-time (Fast and Actionable Data) is set to revolutionise the understanding and optimisation of individuals’ experiences in their daily lives.

This huge potential however comes with a fundamental ethical concern around the use and sharing of this data and this is something must respect. We have placed vigilance on this issue at the very heart of our strategy and we will ensure the ethical and transparent collection of “real” life data, as part of what we call our “Green Data” approach.

This use must enable the establishment of a balance between the collected data entrusted to us and the services offered to the individual. It is going to transform mass digital communication into localised, personalised and projected interactions. It is also going to make it possible to adapt spaces as their uses evolve, a strategic challenge in optimising the management of assets.

Whilst respecting and ensuring the security of personal information, the universal nature of this “physical data” must make it possible to create a contextual intelligence that is of value to both companies and to the individuals themselves in order to react in a relevant manner for all situations experienced in “real” life.